Curiosity - Artificial

VARIABLESCuriosity rewards, Intrinsic rewards

DOMAINS: Artificial intelligence

Contributors: Patricia McKenna

DEVELOPERSJürgen Schmidhuber
(early 1990s)

BACKGROUND

Artificial curiosity theory
- "believes algorithms can be written that allow the programming of
curiosity itself.What's interesting?
Many interesting things are unexpected, but not all unexpected things are
interesting or surprising. According to Schmidhuber's formal theory of surprise
& novelty & interestingness & attention & creativity &
intrinsic motivation, curious agents are interested in learnable but yet
unknown regularities, and get bored by both predictable and inherently
unpredictable things. His active reinforcement learners
translate mismatches between expectations and reality into curiosity rewards or
intrinsic rewards for curious, creative, exploring agents which like to observe
/ create truly surprising aspects of the world, to learn novel patterns".

Singularity
Summit"in our research,
virtual and real worlds actually complement each other. We use machine learning
and artificial curiosity to learn or improve simulations of the real world,
then train the robot in the sim to achieve desirable goals"."Fundamental Principle of Artificial
Curiosity and Creativity: Reward the reward- optimizing controller for actions
yielding data that cause improvements of the adaptive predictor or data
compressor! (Formulated in the early 1990s; basis of much of the recent work in
Developmental Robotics since 2004) "